Denoising of Hyperspectral Images Using Group Low-Rank Representation
نویسندگان
چکیده
منابع مشابه
A New Low-Rank Representation Based Hyperspectral Image Denoising Method for Mineral Mapping
Hyperspectral imaging technology has been used for geological analysis for many years wherein mineral mapping is the dominant application for hyperspectral images (HSIs). The very high spectral resolution of HSIs enables the identification and the diagnosis of different minerals with detection accuracy far beyond that offered by multispectral images. However, HSIs are inevitably corrupted by no...
متن کاملWhen Low Rank Representation Based Hyperspectral Imagery Classification Meets Segmented Stacked Denoising Auto-Encoder Based Spatial-Spectral Feature
When confronted with limited labelled samples, most studies adopt an unsupervised feature learning scheme and incorporate the extracted features into a traditional classifier (e.g., support vector machine, SVM) to deal with hyperspectral imagery classification. However, these methods have limitations in generalizing well in challenging cases due to the limited representative capacity of the sha...
متن کاملHyperspectral image denoising and anomaly detection based on low-rank and sparse representations
The very high spectral resolution of Hyperspectral Images (HSIs) enables the identification of materials with subtle differences and the extraction subpixel information. However, the increasing of spectral resolution often implies an increasing in the noise linked with the image formation process. This degradation mechanism limits the quality of extracted information and its potential applicati...
متن کاملImage Denoising Using Low Rank Minimization With Modified Noise Estimation
Recently, the application of low rank minimization to image denoising has shown remarkable denoising results which are equivalent or better than those of the existing state-of-the-art algorithms. However, due to iterative nature of low rank optimization, estimation of residual noise is an essential requirement after each iteration. Currently, this noise is estimated by using the filtered noise ...
متن کاملObject recognition in hyperspectral images using Binary Partition Tree representation
In this work, an image representation based on Binary Partition Tree is proposed for object detection in hyperspectral images. This hierarchical region-based representation can be interpreted as a set of hierarchical regions stored in a tree structure, which succeeds in presenting: (i) the decomposition of the image in terms of coherent regions and (ii) the inclusion relations of the regions in...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
سال: 2016
ISSN: 1939-1404,2151-1535
DOI: 10.1109/jstars.2016.2531178